Abstract

Reliable operation of power systems depends highly on the condition of power transformers, hence making their condition monitoring top priority. Partial discharge (PD) is among the most common and deteriorative faults in a power transformer. PDs cause progressive degradation of the insulation system of transformers, and may lead to catastrophic failures, if no countermeasure is taken. The ultrahigh frequency (UHF) measurement technique is capable of detecting and localizing PDs inside a power transformer. In this method, electromagnetic waves emitted from the PD fault are captured by UHF probes. From the difference in arrival times of the signals, captured by the probes, the location of the PD fault can be obtained. To date, several researches have attempted to introduce a method for arrival time detection. However, these methods are not capable of providing an acceptable location for the PD inside the transformer tank for each set of the received signals. This reduction in the provided PD locations by the signal sets is exacerbated when the electromagnetic waves encounter more barriers in their path to the UHF probes. This contribution is aimed at optimizing the number of selected signal sets that yield an acceptable location for the PD, in order to improve the localization accuracy. The PD signals are denoised using wavelet filtering, and the arrival time detection method is then applied to the denoised signals. The obtained PD locations are subsequently assessed to estimate the PD fault position with the highest possible accuracy. This research is accompanied by experimental measurements to acquire the location of a PD source inside a specially designed transformer tank and evaluate the proposed algorithm. A novel approach regarding the optimal selection of the captured signal sets is presented and the results are compared.

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